整合生物学先验信息的全基因组选择方法及其在家畜育种中的应用进展

doi:10.11843/j.issn.0366-6964.2021.012.001

畜牧兽医学报 ›› 2021, Vol. 52 ›› Issue (12): 3323-3334.doi: 10.11843/j.issn.0366-6964.2021.012.001

整合生物学先验信息的全基因组选择方法及其在家畜育种中的应用进展

袁泽湖^1,2, 葛玲³, 李发弟², 乐祥鹏^2*, 孙伟^1,3*

1. 扬州大学教育部农业与农产品安全国际合作联合实验室, 扬州 225000;
2. 兰州大学草地农业科技学院草地农业生态系统国家重点实验室/农业农村部草牧业创新重点实验室/教育部草地农业工程研究中心, 兰州 730020;
3. 扬州大学动物科学与技术学院, 扬州 225000

收稿日期:2021-04-06 出版日期:2021-12-25 发布日期:2021-12-22
通讯作者: 孙伟,主要从事动物遗传育种与繁育研究,E-mail:dkxmsunwei@163.com;乐祥鹏,主要从事动物遗传育种研究,E-mail:lexp@lzu.edu.cn
作者简介:袁泽湖(1988-),男,重庆綦江人,助理研究员,博士,主要从事动物遗传育种研究,E-mail:yuanzehu@yzu.edu.cn
基金资助:
国家自然科学基金国际合作项目（32061143036）；国家自然科学基金面上项目（31872333；32172689）；江苏省农业重大新品种创制项目（PZCZ201739）；江苏省重点研发计划（现代农业）项目（BE2018354）；江苏省农业科技自主创新资金项目（CX（18）2003）；江苏省自然科学基金青年基金项目（BK20210811）；扬州市重点研发计划（YZ2021055）

The Method of Genomic Selection by Integrating Biological Prior Information and Its Application in Livestock Breeding

YUAN Zehu^1,2, GE Ling³, LI Fadi², YUE Xiangpeng^2*, SUN Wei^1,3*

1. Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education, Yangzhou University, Yangzhou 225000, China;
2. Grassland Agriculture Engineering Center of Ministry of Education, Key Laboratory of Grassland Livestock Industry Innovation of Ministry of Agriculture and Rural Affairs, State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China;
3. College of Animal Science and Technology, Yangzhou University, Yangzhou 225000, China

Received:2021-04-06 Online:2021-12-25 Published:2021-12-22

摘要/Abstract

摘要： 相较于传统的育种方法，全基因组选择（genomic selection，GS）通过对拟留种的个体进行早期选择和增加选择的准确性进而加快育种的遗传进展。通过改进GS方法无法再缩短育种的世代间隔，因而如何提高GS的准确性以获得额外的遗传进展一直是GS研究的核心问题。当前，各种组学技术不断成熟，从公开的资料或前期的研究积累获取生物学先验信息已比较容易。因而，如何在GS模型中整合已知的先验信息进而提高GS的准确性以获得额外的遗传进展成为当前育种研究的热点问题。本文对生物学先验信息的类型以及整合先验信息的GS方法进行综述，探讨了这些方法在家畜育种中的应用和前景，以期为家畜育种中开展整合生物学先验信息的GS研究提供借鉴与参考。

关键词: 生物学先验信息, 全基因组选择, 家畜育种, 多组学

Abstract: Compared to the traditional breeding methods, genomic selection (GS) accelerates the genetic progress of breeding by early selection and increasing the accuracy of selection for the individuals to be retained. It is unlikely shortened the generation interval by improving the GS methods. Therefore, how to improve the accuracy of GS to obtain additional genetic progress is the core issue of GS research. With the development of omics technology, it becomes possible to obtain multi-omics biological prior information from the public available databases or the in-house research. Therefore, how to integrate this useful biological prior information into GS models to improve the accuracy of GS has become an important topic in current animal breeding research. In this paper, the types of biological prior information and the GS methods that can integrate prior information is reviewed. Then,the application and prospects of these methods applied to livestock breeding is discussed. It is expected to provide useful information for the GS research that integrates biological prior information on livestock breeding.

Key words: biological prior information, genomic selection, livestock breeding, multi-omics

中图分类号:

S813.2

袁泽湖, 葛玲, 李发弟, 乐祥鹏, 孙伟. 整合生物学先验信息的全基因组选择方法及其在家畜育种中的应用进展[J]. 畜牧兽医学报, 2021, 52(12): 3323-3334.

YUAN Zehu, GE Ling, LI Fadi, YUE Xiangpeng, SUN Wei. The Method of Genomic Selection by Integrating Biological Prior Information and Its Application in Livestock Breeding[J]. Acta Veterinaria et Zootechnica Sinica, 2021, 52(12): 3323-3334.

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整合生物学先验信息的全基因组选择方法及其在家畜育种中的应用进展

The Method of Genomic Selection by Integrating Biological Prior Information and Its Application in Livestock Breeding

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